914 resultados para operating windows


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This paper describes the development of a simulation model for operating theatres. Elective patient scheduling is complicated by several factors; stochastic demand for resources due to variation in the nature and severity of a patient’s illness, unexpected complications in a patient’s course of treatment and the arrival of non-scheduled emergency patients which compete for resources. Extend simulation software was used for its ability to represent highly complex systems and analyse model outputs. Patient arrivals and lengths of surgery are determined by analysis of historical data. The model was used to explore the effects increasing patient arrivals and alternative elective patient admission disciplines would have on the performance measures. The model can be used as a decision support system for hospital planners.

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Prognostics and asset life prediction is one of research potentials in engineering asset health management. We previously developed the Explicit Hazard Model (EHM) to effectively and explicitly predict asset life using three types of information: population characteristics; condition indicators; and operating environment indicators. We have formerly studied the application of both the semi-parametric EHM and non-parametric EHM to the survival probability estimation in the reliability field. The survival time in these models is dependent not only upon the age of the asset monitored, but also upon the condition and operating environment information obtained. This paper is a further study of the semi-parametric and non-parametric EHMs to the hazard and residual life prediction of a set of resistance elements. The resistance elements were used as corrosion sensors for measuring the atmospheric corrosion rate in a laboratory experiment. In this paper, the estimated hazard of the resistance element using the semi-parametric EHM and the non-parametric EHM is compared to the traditional Weibull model and the Aalen Linear Regression Model (ALRM), respectively. Due to assuming a Weibull distribution in the baseline hazard of the semi-parametric EHM, the estimated hazard using this model is compared to the traditional Weibull model. The estimated hazard using the non-parametric EHM is compared to ALRM which is a well-known non-parametric covariate-based hazard model. At last, the predicted residual life of the resistance element using both EHMs is compared to the actual life data.

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Films found on the windows of residential buildings have been studied. The main aim of the paper was to assess the roles of the films in the accumulation of potentially toxic chemicals in residential buildings. Thus the elemental and polycyclic aromatic hydrocarbon compositions of the surface films from the glass windows of eighteen residential buildings were examined. The presence of sample amounts of inorganic elements (4.0–1.2 × 106 μg m−2) and polycyclic aromatic hydrocarbons in the films (BDL - 620.1 ng m−2) has implications for human exposure and the fate of pollutants in the urban environment. To facilitate the interpretation of the results, data matrices consisting of the chemical composition of the films and the building characteristics were subjected to multivariate data analysis methods, and these revealed that the accumulation of the chemicals was strongly dependent on building characteristics such as the type of glass used for the window, the distance from a major road, age of the building, distance from an industrial activity, number of smokers in the building and frequency of cooking in the buildings. Thus, building characteristics which minimize the accumulation of pollutants on the surface films need to be encouraged.

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While recent research has provided valuable information as to the composition of laser printer particles, their formation mechanisms, and explained why some printers are emitters whilst others are low emitters, fundamental questions relating to the potential exposure of office workers remained unanswered. In particular, (i) what impact does the operation of laser printers have on the background particle number concentration (PNC) of an office environment over the duration of a typical working day?; (ii) what is the airborne particle exposure to office workers in the vicinity of laser printers; (iii) what influence does the office ventilation have upon the transport and concentration of particles?; (iv) is there a need to control the generation of, and/or transport of particles arising from the operation of laser printers within an office environment?; (v) what instrumentation and methodology is relevant for characterising such particles within an office location? We present experimental evidence on printer temporal and spatial PNC during the operation of 107 laser printers within open plan offices of five buildings. We show for the first time that the eight-hour time-weighted average printer particle exposure is significantly less than the eight-hour time-weighted local background particle exposure, but that peak printer particle exposure can be greater than two orders of magnitude higher than local background particle exposure. The particle size range is predominantly ultrafine (< 100nm diameter). In addition we have established that office workers are constantly exposed to non-printer derived particle concentrations, with up to an order of magnitude difference in such exposure amongst offices, and propose that such exposure be controlled along with exposure to printer derived particles. We also propose, for the first time, that peak particle reference values be calculated for each office area analogous to the criteria used in Australia and elsewhere for evaluating exposure excursion above occupational hazardous chemical exposure standards. A universal peak particle reference value of 2.0 x 104 particles cm-3 has been proposed.

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A hospital consists of a number of wards, units and departments that provide a variety of medical services and interact on a day-to-day basis. Nearly every department within a hospital schedules patients for the operating theatre (OT) and most wards receive patients from the OT following post-operative recovery. Because of the interrelationships between units, disruptions and cancellations within the OT can have a flow-on effect to the rest of the hospital. This often results in dissatisfied patients, nurses and doctors, escalating waiting lists, inefficient resource usage and undesirable waiting times. The objective of this study is to use Operational Research methodologies to enhance the performance of the operating theatre by improving elective patient planning using robust scheduling and improving the overall responsiveness to emergency patients by solving the disruption management and rescheduling problem. OT scheduling considers two types of patients: elective and emergency. Elective patients are selected from a waiting list and scheduled in advance based on resource availability and a set of objectives. This type of scheduling is referred to as ‘offline scheduling’. Disruptions to this schedule can occur for various reasons including variations in length of treatment, equipment restrictions or breakdown, unforeseen delays and the arrival of emergency patients, which may compete for resources. Emergency patients consist of acute patients requiring surgical intervention or in-patients whose conditions have deteriorated. These may or may not be urgent and are triaged accordingly. Most hospitals reserve theatres for emergency cases, but when these or other resources are unavailable, disruptions to the elective schedule result, such as delays in surgery start time, elective surgery cancellations or transfers to another institution. Scheduling of emergency patients and the handling of schedule disruptions is an ‘online’ process typically handled by OT staff. This means that decisions are made ‘on the spot’ in a ‘real-time’ environment. There are three key stages to this study: (1) Analyse the performance of the operating theatre department using simulation. Simulation is used as a decision support tool and involves changing system parameters and elective scheduling policies and observing the effect on the system’s performance measures; (2) Improve viability of elective schedules making offline schedules more robust to differences between expected treatment times and actual treatment times, using robust scheduling techniques. This will improve the access to care and the responsiveness to emergency patients; (3) Address the disruption management and rescheduling problem (which incorporates emergency arrivals) using innovative robust reactive scheduling techniques. The robust schedule will form the baseline schedule for the online robust reactive scheduling model.

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In this video, words emerge out of an abstract, ‘digital’, animated horizon line. The words are accompanied by a female voice-over who narrates a seductive relaxation and visualization activity. This work examines the nature of consciousness and identity in a contemporary context. It mixes the languages of meditation, new age philosophy and pop-psychology. Drawing on Zygmunt Bauman’s theoretical work on “liquid modernity”, this work questions how and where we find space for contemplation and reflection in a contemporary context increasingly defined by temporary social bonds and consumer choices.

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Network RTK (Real-Time Kinematic) is a technology that is based on GPS (Global Positioning System) or more generally on GNSS (Global Navigation Satellite System) observations to achieve centimeter-level accuracy positioning in real time. It is enabled by a network of Continuously Operating Reference Stations (CORS). CORS placement is an important problem in the design of network RTK as it directly affects not only the installation and running costs of the network RTK, but also the Quality of Service (QoS) provided by the network RTK. In our preliminary research on the CORS placement, we proposed a polynomial heuristic algorithm for a so-called location-based CORS placement problem. From a computational point of view, the location-based CORS placement is a largescale combinatorial optimization problem. Thus, although the heuristic algorithm is efficient in computation time it may not be able to find an optimal or near optimal solution. Aiming at improving the quality of solutions, this paper proposes a repairing genetic algorithm (RGA) for the location-based CORS placement problem. The RGA has been implemented and compared to the heuristic algorithm by experiments. Experimental results have shown that the RGA produces better quality of solutions than the heuristic algorithm.

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Optimal design methods have been proposed to determine the best sampling times when sparse blood sampling is required in clinical pharmacokinetic studies. However, the optimal blood sampling time points may not be feasible in clinical practice. Sampling windows, a time interval for blood sample collection, have been proposed to provide flexibility in blood sampling times while preserving efficient parameter estimation. Because of the complexity of the population pharmacokinetic models, which are generally nonlinear mixed effects models, there is no analytical solution available to determine sampling windows. We propose a method for determination of sampling windows based on MCMC sampling techniques. The proposed method attains a stationary distribution rapidly and provides time-sensitive windows around the optimal design points. The proposed method is applicable to determine sampling windows for any nonlinear mixed effects model although our work focuses on an application to population pharmacokinetic models.

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Exposure to air pollution during pregnancy is a potential cause of adverse birth outcomes such as preterm birth and stillbirth. The risk of exposure may be greater during vulnerable windows of the pregnancy which might only be weeks long. We demonstrate a method to find these windows based on smoothing the risk of weekly exposure using conditional autoregression. We use incidence density sampling to match cases with adverse birth outcomes to controls whose gestation lasted at least as long as the case. This matching means that cases and controls are have equal length exposure periods, rather than comparing, for example, cases with short gestations to controls with longer gestations. We demonstrate the ability of the method to find vulnerable windows using two simulation studies. We illustrate the method by examining the association between particulate matter air pollution and stillbirth in Brisbane, Australia.

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We test the broken windows theory using a field experiment in a shared area of an academic workplace(the department common room). More specifically, we explore academics’ and postgraduate students’ behavior under an order condition (a clean environment) and a disorder condition (a messy environment). We find strong evidence that signs of disorderly behavior trigger littering: In 59% of the cases, subjects litter in the disorder treatment as compared to 18% in the order condition. These results remain robust in a multivariate analysis even when controlling for a large set of factors not directly examined by previous studies. Overall, when academic staff and postgraduate students observe that others have violated the social norm of keeping the common room clean, all else being equal, the probability of littering increases by around 40%.

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In this paper we demonstrate how to monitor a smartphone running Symbian operating system and Windows Mobile in order to extract features for anomaly detection. These features are sent to a remote server because running a complex intrusion detection system on this kind of mobile device still is not feasible due to capability and hardware limitations. We give examples on how to compute relevant features and introduce the top ten applications used by mobile phone users based on a study in 2005. The usage of these applications is recorded by a monitoring client and visualized. Additionally, monitoring results of public and self-written malwares are shown. For improving monitoring client performance, Principal Component Analysis was applied which lead to a decrease of about 80 of the amount of monitored features.

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The control paradigms of the distributed generation (DG) sources in the smart grid are realised by either utilising virtual power plant (VPP) or by employing MicroGrid structures. Both VPP and MicroGrid are presented with the problem of control of power flow between their comprising DG sources. This study depicts this issue for VPP and proposes a novel and improved universal active and reactive power flow controllers for three-phase pulse width modulated voltage source inverters (PWM-VSI) operating in the VPP environment. The proposed controller takes into account all cases of R-X relationship, thus allowing it to function in systems operating at high, medium (MV) and low-voltage (LV) levels. Also proposed control scheme for the first time in an inverter control takes into account the capacitance of the transmission line which is an important factor to accurately represent medium length transmission lines. This allows the proposed control scheme to be applied in VPP structures, where DG sources can operate at MV LV levels over a short/medium length transmission line. The authors also conducted small signal stability analysis of the proposed controller and compared it against the small signal study of the existing controllers.